Software Automatic Tuning
From Concepts to State-of-the-Art Results
(Sprache: Englisch)
This invaluable reference summarizes the latest research efforts on automatic performance tuning, a new methodology which maximizes software performance in any computing environment. It provides programmers with practical tips on writing their own AT software.
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This invaluable reference summarizes the latest research efforts on automatic performance tuning, a new methodology which maximizes software performance in any computing environment. It provides programmers with practical tips on writing their own AT software.
Klappentext zu „Software Automatic Tuning “
Automatic Performance Tuning is a new software paradigm which enables software to be high performance in any computing environment. Its methodologies have been developed over the past decade, and it is now rapidly growing in terms of its scope and applicability, as well as in its scientific knowledge and technological methods. Software developers and researchers in the area of scientific and technical computing, high performance database systems, optimized compilers, high performance systems software, and low-power computing will find this book to be an invaluable reference to this powerful new paradigm.
Inhaltsverzeichnis zu „Software Automatic Tuning “
Software Automatic Tuning: Concepts and State-of-the-Art Results.- Achievements in Scientific Computing.- ATLAS Version 3.9: Overview and Status.- Autotuning Method for Deciding Block Size Parameters in Dynamically Load-Balanced BLAS.- Automatic Tuning for Parallel FFTs.- Dynamic Programming Approaches to Optimizing the Blocking Strategy for Basic Matrix Decompositions.- Automatic Tuning of the Division Number in the Multiple Division Divide-and-Conquer for Real Symmetric Eigenproblem.- Automatically Tuned Mixed-Precision Conjugate Gradient Solver.- Automatically Tuned Sparse Eigensolvers.- Systematic Performance Evaluation of Linear Solvers Using Quality Control Techniques.- Application of Alternating Decision Trees in Selecting Sparse Linear Solvers.- Toward Automatic Performance Tuning for Numerical Simulations in the SILC Matrix Computation Framework.- Exploring Tuning Strategies for Quantum Chemistry Computations.- Automatic Tuning of CUDA Execution Parameters for Stencil Processing.- Static Task Cluster Size Determination in Homogeneous Distributed Systems.- Evolution to a General Paradigm.- Algorithmic Parameter Optimization of the DFO Method with the OPAL Framework.- A Bayesian Method of Online Automatic Tuning.- ABCLibScript: A Computer Language for Automatic Performance Tuning.- Automatically Tuning Task-Based Programs for Multicore Processors.- Efficient Program Compilation Through Machine Learning Techniques.- Autotuning and Specialization: Speeding up Matrix Multiply for Small Matrices with Compiler Technology.
Bibliographische Angaben
- 2010, XIV, 377 Seiten, Maße: 16,7 x 24,4 cm, Gebunden, Englisch
- Herausgegeben: Ken Naono, Keita Teranishi, John Cavazos, Reiji Suda
- Verlag: Springer, Berlin
- ISBN-10: 1441969349
- ISBN-13: 9781441969347
Sprache:
Englisch
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